The value of electronic sensing devices for sensing physiological parameters of a person has been known in the medical industry for many years. To this end, many sensing devices have been developed that can be adhered or mechanically attached to a person's body at specific locations to sense specific parameter such as heart beat, breathing rate, temperature, blood flow, perspiration rate, etc. In addition, many applications have been developed to use sensed physiological parameters data to determine other conditions of a person. In some cases, physicians or other health care specialists have used sensed data to detect physical conditions of clients and to advise clients on lifestyle changes designed to help clients live healthier lives. In other cases, systems have been developed for home use to monitor biometric parameters and provide feedback to a person or the person's physician to indicate current health conditions or physiological parameter trending over time. In some cases sensed data has been used by other entities such as, for instance, insurance companies, to customize policies based on perceived health of particular persons.
One problem with early sensing systems was that those systems generally required a person to be located at a specific location in order to use the sensing systems. For instance, in some cases a person was required to be at a medical facility to be connected up to a sensing system. As another instance, in some cases a person was required to be at home where a processor and sensor assembly was located in order to use a sensing system.
Recently, with the advent of smaller electronic devices, smaller power sources and portable interface devices (e.g., smartphones, pad-type devices, etc.), many personal portable sensing devices have been developed along with associated applications that can be used by individuals or proxies (e.g., a primary care physician) to track physiological parameters over long periods of time outside of a hospital or home environment. For instance, there are many wrist mountable devices on the market today which monitor various physiological parameters and provide those parameters to an application run on a computing device (e.g., a pad-type device) which in turn processes the received data and outputs the data or other data derived therefrom to the person wearing the device for consideration. In many cases the idea here is to make a person aware of their physiological parameters and encourage a lifestyle change or at least maintenance of a healthy lifestyle that currently exists. Thereafter, the person receiving the data is required to act based on the received data to change or maintain their lifestyle. One particular advantage of wearable devices is that those devices may be in contact with a person's body for many hours each day and therefore data can be obtained over long periods of time and during different activities (e.g., exercise, relaxation, cognitively stressful periods, etc.). Thus, these devices that are in contact with a person's body over the long term, can feed new and more complex applications based on long term parameter values.
In addition to physiological parameter sensors, other sensor systems and devices have been developed for sensing various aspects of a person's behavior. For instance, wrist mounted or otherwise wearable pedometers have been developed that can estimate or count the number of steps a person takes during the course of a day or a distance traveled during a day or during an event (e.g., during a run). Other sensors have been developed to sense other behaviors or activities of a person (e.g., sitting, standing, etc.).
One problem with wearable devices like wrist mounted devices is that many people simply do not like wearing electronic devices. For instance, in many cases these devices are relatively large and clunky and can physically get in the way of some activities. As another instance, many wearable devices have an industrial look and feel and therefore are aesthetically unappealing. Still one other problem with wearable devices is that many of these devices are expensive and therefore cannot be personally purchased by many people that would like to take advantage of the functionality associated therewith. Still one other problem with these devices is that they typically require batteries and therefore, at least periodically, require some affirmative step by a user to initiate a recharge cycle. In most cases recharging require removal of the device and connection to some stationary charging station. Still one other problem with these devices is that they require a user to react correctly to generated data in order to make a change in the person's health (i.e., if a person is too sedentary, the person needs to become more active to improve their health).
One way to overcome many of the problems associated with wearable sensing devices is to provide sensing devices within a person's environment that are separate from the person but in proximity such that the devices can still sense physiological parameters and behaviors. Optimal places for sensors are locations where a person is located for a long time. For instance, most people spend one quarter to one third of their time in their beds. For this reason, some systems have been developed to place at least some types of sensors in mattress or other bed structure. As another instance, many people spend at least some time each day driving in their vehicles. For this reason, some systems have been developed that include sensors proximate a vehicle driver for sensing biometrics.
For many people, the place they spend most of their time after their bed is at work. For instance, many people spend eight, ten, or more hours at a facility operated by their employer. In many cases when a person spends a lot of time at work, most of that time is spent in a relatively small area. For example, many employees spend most of their time at work in a personal office or at a personal workstation or in a temporarily selected office or workstation. In fact, in many cases, a person spends most of her time in only a portion of an office or space proximate a work station. For instance, in many cases, an employee will be seated in a task chair proximate a desk or workstation where the chair is only moved within a small area (e.g., 5 by 5 feet) throughout a work day. In fact, in many cases a hard plastic floor mat is provided under a task chair to facilitate movement of the chair on casters adjacent a desk or workstation. Here, in most cases, a person is inclined to use their chair on the mat within the relatively small space (e.g., 5 by 5 feet) defined thereby. In cases where there is no mat, a person still typically only uses their chair in a space immediately adjacent a work station. Thus, in many cases each employee within an employer's facility spends most of her time within a relatively small defined space.
With respect to poor habits or behaviors or physiological parameters that adversely affect a person's health, it may be that some unhealthy activities for certain people occur at work. For instance, it is known that it is unhealthy for a person to remain stationary for long periods of time. Nevertheless, many people sit in a task chair for hours at a time without standing, walking or other physical activity. As another instance, it is known that it may be unhealthy to remain in the same position for a long time as such inaction puts undue stress on certain parts of a person's body which, in many cases, ultimately results in some form of pain. Nevertheless, many people working at a workstation maintain a single position, often times with poor posture, for hours on end without significant movement.
One other behavior that is often more prevalent within a working environment than in home environments is poor eating. In this regard, while people can control the foods they bring into their homes and often can spend additional time seeking out and preparing healthy foods when not at work, time restraints and lack of cooking resources often mean that eating habits at work facilities suffer appreciably. Poor eating habits are exacerbated in work environments where co-workers often bring unhealthy options to share during holidays or special occasions when there is added pressure to participate in festivities.
Thus, for various reasons it makes sense to provide physiological parameter sensors and behavioral sensors in work spaces used by people. First, many people are located in their work spaces for long and continuous periods and therefore instantaneous and long term physiological parameter data can be collected and analyzed. Second, by providing sensors to sense physiological and behavioral data within a work space, that data can be collected during normal daily activities to get a different view of a person's health and behavior. Third, by detecting parameters and behavior essentially in real time in a work environment, feedback can be provided to a person whenever some parameter is outside a range of acceptable values or when an altered behavior is determined to be relatively optimal.
A typical workstation includes, among other things, a desk or table that forms at least one work surface and a task chair adjacent thereto. In many cases a workstation will also include some type of stationary computing device such as a computer with a keyboard for user input and a flat panel or other type of display screen for providing information to a workstation user. A task chair is the one workstation device or assembly that most workstation users are in contact with most of the time while using a workstation. For this reason, locating sensors within a chair seat for sensing basic information such as presence, temperature, etc., is particularly advantageous and is generally known.
One problem with placing a sensor in a mobile chair has to do with how to get power to the sensors and how to get data from the sensors to a system processor for analysis, storage and reporting.
Thus, what is needed is a system that can sense many different physiological parameters of a person within a workspace and can use sensed parameter values to perform various functions. More specifically, what is needed is a system including sensors provided within furniture affordances that are proximate a workspace user and that optimally make contact (either direct or through clothing) with a person during workspace use so that reliable physiological parameter data can be obtained. In the case of a task chair, what is needed is a way to deliver power to the chair for powering sensors that is efficient and extremely easy to use, optimally requiring little if any activity from a chair user to provide the power. In addition, it would be advantageous if a chair could automatically adjust operations as a function of sensed physiological parameters or behaviors of a user of the chair in ways intended to increase overall chair user health and wellbeing.
With an enterprise facility, second to the chair, the affordance most people are near or touching most often and for extended periods of time is a workstation table. Thus, it would also be advantageous to integrate sensor devices within a workstation table assembly in addition to or instead of in a chair.
One particularly useful way to positively affect a chair user's health is to, in many cases, encourage the chair user to get out of the chair, to intermittently stand for periods between sitting periods. To support a user that alternates between standing and sitting, workstations with height adjustable tabletops have been developed. In at least some cases simple reminder systems have been developed that provide reminders to change from sitting to standing and vice versa based on the duration of a workstation tabletop in the sitting and standing positions. For instance, in a simple case, if a user has been sitting for one hour, a reminder may be provided to encourage the user to stand.
While simple sit-stand reminder systems in height adjustable workstations are advantageous, they have several shortcomings. First, in known systems reminder times are based on duration of periods that tabletops are in sit and stand positions. While durations of sit and stand periods are interesting, they only represent a very small amount of information which is simply not a reliable proxy for a station user's current condition. For instance, if a person sits from 10 AM to noon while working at her workstation and then runs for two hours during an extended lunch break and returns to her workstation, a sit-stand reminder system would likely encourage her to stand for some time. Here the encouragement to stand would be based on the two hour sitting period from 10 AM to noon and would ignore the two hour run and, in the context of the run, would simply be bothersome and make no sense.
As another instance, if a station user stands at his station from 11 AM to noon and then attends a two hour lunch meeting where he sits in a conference room for the entire two hour meeting, upon returning to his station, based on the 11 AM to noon standing period and ignoring the two hours of sitting at the meeting, the system would likely recommend a sitting period which again, would be bothersome and make no sense.
Second, the assumption that a workstation user is standing and sitting when a workstation tabletop is at a standing and sitting height, respectively, is often wrong. For instance, in many cases high stools or task chairs may be used at stations to support users in sitting positions while using a standing height tabletop. As another instance, most sit-stand tables only provide a portion of workstation worksurface where other worksurface area is persistently at a sitting height. In these cases, for instance, a height adjustable leg structure may support a rectangular tabletop for height adjustment while one or more other tabletops at a station are persistently at the sitting height. In many cases even when a height adjustable tabletop is high, a station user will use one of the low station worksurfaces while sitting.
As yet another instance, tying reminders to sensed prior sit-stand periods along ignore another source of informative data that could be used to better determine when to suggest user position changes. To this end, a user's schedule, as captured by electronic scheduling software, can be mined for tell-tale signs of the user's physical posture while away from a workstation (e.g., assume the user is sitting when scheduled for meeting in a conference room, assume the user is walking when traveling on campus for 20 minutes between two conference rooms, etc.).
As another instance, simple tabletop height based sit-stand processes fail to take into consideration a user's real time physiological condition such as heart rate, blood pressure, temperature, state of perspiration, breathing condition, etc., and therefore, often times may suggest a position change that could negatively affect a station user's condition. Similarly, basing sit-stand recommendations solely on tabletop height periods ignores a station user's state of mine and can often serve as a distraction that may adversely affect user work product. For instance, where a user is currently deep in thought (e.g., in a state of “flow”), a reminder to change position can often disturb the user's state and therefore adversely affect work product.
Another general shortcoming with known workstations is that many stations include lighting, power, audio and video capabilities that are simply not adjustable to user preferences. For instance, some user's may like ceiling lighting on worksurfaces while others may strongly prefer quiet baroque music while other want background white noise while working. In many cases workstation affordances cannot be adjusted to meet these and other preferences. In cases where affordances are adjustable to meet personal preferences, in many cases users simply do not take the time to set their preferences. This is especially true in the case of workstations that are used by many users or part of a shared hotelling facility space as opposed to in dedicated user workstations.
Yet one other problem with known workstations and furniture affordances that do sense at least some user activities and/or physiological conditions is that user can perceive that their privacy is being invaded. Thus, for instance, if a user's identity has to be known for a system to access personal physiological data needed to drive sit-stand processes, position change processes or other workstation services, many users may view the identity and physiological parameters combination as a personal data privacy violation.